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Apple unveiled Core ML at their WWDC in June, a software framework for letting developers deploy and work with trained machine learning models in apps on all of Apple's platforms—iOS, macOS, tvOS, and watchOS. Core ML is intended to spare developers from having to build all the platform-level plumbing themselves for deploying a model, serving predictions from it, and handling any extraordinary conditions that might arise. But it's also currently a beta product, and one with a highly constrained feature set.
Apple started the Machine Learning Journal in July where you could read posts written by Apple engineers about their work using machine learning technologies to help build innovative products for millions of people around the world. Below is a list of the issues published thus far:
01: Improving the Realism of Synthetic Images
02: Improving Neural Network Acoustic Models by Cross-bandwidth and Cross-lingual Initialization
03: Improving Neural Network Acoustic Models by Cross-bandwidth and Cross-lingual Initialization
04: Inverse Text Normalization as a Labeling Problem
05: Deep Learning for Siri's Voice: On-device Deep Mixture Density Networks for Hybrid Unit Selection Synthesis
06: Real-Time Recognition of Handwritten Chinese Characters Spanning a Large Inventory of 30,000 Characters
07: Hey Siri: An On-device DNN-powered Voice Trigger for Apple's Personal Assistant
08: An On-device Deep Neural Network for Face Detection
On Monday Apple filed for the figurative trademark for Machine Learning as presented below, in green. Their U.S. filing presented the figurative trademark in yellow as presented in our cover graphic. It's unknown at this time if Apple has the trademark color coded for a particular reason.